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The Scientific Method Today

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After evaluating all the evidence, biologist James Watson and biophysicist Francis Crick solved one of nature's greatest puzzles - the structure of the DNA molecule ... the genetic "blueprint" that dictates the traits which living things inherit.

They earned a Nobel Prize for this discovery.

 

Herbert A. Simon, Nobel Laureate, and his associates researched the human problem-solving process.

Through evaluation of the evidence, they arrived at the hypothesis that a great variety of problems could be solved by use of a computer.

Dr. Simon's books contain a wealth of evidence on problem solving and artificial intelligence.

Stage #6 :

EVALUATE the EVIDENCE

By now you should have a list of tentative solutions that are candidates for your educated guess or hypothesis.

This is also the stage for experimenting and testing. The final choice is often called your working hypothesis and will be your Stage #7.

Starting guides to consider before working on each ingredient:

  • Problem: Should it be redefined or reframed?
  • Goals and planning: Any changes? Any new leads or clues? Planning ahead?
  • Goal-referencing approach: Where you started, are at now, and still need to go.
  • Looking back: Have you been using the right attributes, methods, strategies, technologies, plus curious observation? Have you consulted your advisor? Have you had a team meeting? Are you keeping your log up-to-date? Being on the right path is important!
  • Are you using innovation, creativity, watching for surprises? Are you alert to clues and leads?
  • Are you putting thoughts and ideas into writing? Using all available resources?

Evaluating Your Tentative Hypotheses

  • If data on any of these hypotheses is insufficient, gather additional information.
  • Check against any list of criteria, formulas, and routines you have established.
  • It may be helpful to read the information on Ingredient #7 to familiarize yourself with the characteristics and traits your working hypothesis must have.

Also, read Stage #8 to alert you as to how it will have to be challenged.

Tests, Experiments, Strategies, Techniques
& Other Methods of Evaluating

Logical reasoning Mathematical solution Consult literature
Surveys Independent lab test Collaborators
Interviews Expert opinions Controlled experiments
Modeling Concepts correct? Dis-confirming tests
Graphs Improvisation Data base reliable?
Sampling Disqualifying Consider consequences
Speculation. Make predictions Statistical analysis
Simulations Challenge assumptions Design special instruments
"Live It" Computer testing "Anything goes" theory
Visualizing Measuring Need to ripen more?

Chart Your Solutions to Weigh the Evidence

Be more careful and make your choice. Criteria can be graded by as many facets, characteristics or angles as you desire. You can have individual charts or a joint one. Tailor headings to fit your problem.



Possible Comparison Chart

Tentative
Choices

Test Results

Suitability

Feasibility

Acceptability

  #1 #2 #1 #2 #1 #2 #1 #2
Solution A
Against For 30% Okay 60% Okay 50% 90%
Solution B
For Against 50% No 80% No 90% 20%



Evaluate Carefully, but Remember - Perfection Is Not Always Possible

Time, money emergencies, importance, practicalbility, and constraints on human thinking often mean we can't be thorough enough, even though we would like to be.

Thus we must often settle for "good enough." similar descriptions are tolerance of ambiguity, aspiraton level, most optimum not needed, satisfactory versus optional standards, adequate for problem, risk within reason, bounded rationality.

The general principles in considering all your efforts:

Accept uncertainty of solution Perfectionism is not always affordable
"Truth" may not exist Rate: Good--Better--Good enough
Consider community "standards" Precision - important in science
Waste no time on little differences No excuse for sloppy work
No single best solution may exist No better action to take


A good base of actual experience or reading of toher people's experience will be of great value in making a quick decision on matters of minor importance, but remember ifyou makedecisions on wrong "facts," what follows are wrong decisions.

Learn to evaluate as - good, better, good enough, or not good enough - and search for further data keeping in mind costs vs. benefits.


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Copyright © 2000, Norman W. Edmund - All Rights Reserved

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